Year: 2010
Type: article
Abstract: Emotion can be studied by measuring physiological, behavioral, and verbal responses to specific stimuli. In current research, it is most common to use visual stimuli to measure the emotional response. One of the most common sets of stimuli used for this purpose is the International Affective Picture Systems (IAPS). An additional set of stimuli, the International Affective Digital Sounds (IADS), was created to be an auditory equivalent of the IAPS. The present study sought to compare the emotional response (measured with Heart Rate, Skin Conductance, and a self-report measure of emotion called the SAM) to sounds from the IADS and images from the IAPS. The self-report measure has participants rate each stimulus for arousal, valence, dominance, and interestingness by using a nine point scale anchored at one end by calm, unpleasant, not in control, and boring and at the other by excited, pleasant, in full control, and riveting, respectively. The present study also looked at differences in emotional response to sounds and images when they were presented in a pure block (all images and then all sounds or reverse) compared to a mixed block (a block of sounds and images, followed by a block of sounds and images). There were a total of 40 participants (34 female, 4 male; mean age 27.08), all of whom were recruited from a local university. Results revealed a significant difference (p < .05) in the heart rate and skin conductance response to sounds versus images. There was also a significant (p < .05) difference in self-reported arousal and dominance to images and sounds. Furthermore, there was a significant difference (p < .05) between the Pure Stimulus and Mixed Stimulus groups for heart rate and self-reported arousal and dominance. Results from this study do not support the theory that auditory and visual stimuli evoke similar physiological and self-reported emotional responses. Results also suggest that stimulus presentation may play a role in the observed or perceived difference in emotional response.
Author: Amy Pitchforth
Language: English
Topic: Emotion and Mood Recognition
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2531061377